The More Things Change, The More they Stay the Same: Border Governance and Resistance along Mexico’s Southern Border with Guatemala
Bibliographic record
Abstract
With the politics of borders, the socio-economic divide between the United States and Mexico is evident. The geographic proximity to the U.S. makes the Mexico–Guatemala border an extension of the U.S. border enforcement regime. This article argues that the politics surrounding the U.S.–Guatemala border have not necessarily changed, because, at the core, the main objective of these border governance practices is to stop the movement of undesirable bodies (Khosravi 2011). Further, the article argues that the practices of containment force migrants to resist through their movement and seek strategies of survival. By comparing the administrations of Peña Nieto and López Obrador (AMLO) and analyzing the survival strategy of migrant “caravans” through border policy analysis and fieldwork conducted in 2014, I show that this border is a site of struggle between the state’s power and migrants’ forms of resistance. I find that border tactics are influenced by U.S. border enforcement requirements of increased militarization and policing, but also aim to restrict and control certain populations. The result is the perpetual securitization of people and the militarization of pathways. Migrants, however, also employ forms of organizing such as travelling in mass groups to achieve safe passage, thus exercising their agency through movement. The bordering practices and the forms of resistance indicate that this border is a constant site of struggle that requires further examination.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".